Temporal variability corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) surface soil moisture: case study in Little River Region, Georgia, U. S.

Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E\u27s limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R-2 values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques

Temporal Variability Corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) Surface Soil Moisture: Case Study in Little River Region, Georgia, U.S.

Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E’s limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R2 values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques

Remote sensing observatory validation of surface soil moisture using Advanced Microwave Scanning Radiometer E, Common Land Model, and ground based data: Case study in SMEX03 Little River Region, Georgia, U.S.

Optimal soil moisture estimation may be characterized by intercomparisons among remotely sensed measurements, ground‐based measurements, and land surface models. In this study, we compared soil moisture from Advanced Microwave Scanning Radiometer E (AMSR‐E), ground‐based measurements, and a Soil‐Vegetation‐Atmosphere Transfer (SVAT) model for the Soil Moisture Experiments in 2003 (SMEX03) Little River region, Georgia. The Common Land Model (CLM) reasonably replicated soil moisture patterns in dry down and wetting after rainfall though it had modest wet biases (0.001–0.054 m3/m3) as compared to AMSR‐E and ground data. While the AMSR‐E average soil moisture agreed well with the other data sources, it had extremely low temporal variability, especially during the growing season from May to October. The comparison results showed that highest mean absolute error (MAE) and root mean squared error (RMSE) were 0.054 and 0.059 m3/m3 for short and long periods, respectively. Even if CLM and AMSR‐E had complementary strengths, low MAE (0.018–0.054 m3/m3) and RMSE (0.023–0.059 m3/m3) soil moisture errors for CLM and soil moisture low biases (0.003–0.031 m3/m3) for AMSR‐E, care should be taken prior to employing AMSR‐E retrieved soil moisture products directly for hydrological application due to its failure to replicate temporal variability. AMSR‐E error characteristics identified in this study should be used to guide enhancement of retrieval algorithms and improve satellite observations for hydrological sciences

Assessment of clear and cloudy sky parameterizations for daily downwelling longwave radiation over different land surfaces in Florida, USA

Clear sky downwelling longwave radiation (Rldc) and cloudy sky downwelling longwave radiation (Rld) formulas were tested across eleven sites in Florida. The Brunt equation, using air vapor pressure and temperature measurements, provides the best Rldc estimates with a root mean square error of less than around 12 Wm−2 across all sites. The Crawford and Duchon\u27s cloudiness factor with Brunt equation is recommended for Rld calculations. This combined approach requires no local calibration and estimates Rld with a root mean square error of less than around 13 Wm−2 and squared correlation coefficients that typically exceed 0.9

Small Cues Change Savings Choices

In randomized field experiments, we embedded one- to two-sentence anchoring, goal-setting, or savings threshold cues in emails to employees about their 401(k) savings plan. We find that anchors increase or decrease 401(k) contribution rates by up to 1.9% of income. A high savings goal example raises contribution rates by up to 2.2% of income. Highlighting a higher savings threshold in the match incentive structure raises contributions by up to 1.5% of income relative to highlighting the lower threshold. Highlighting the maximum possible contribution rate raises contribution rates by up to 2.9% of income among low savers.

Homeless Population Enumeration

There is currently very limited information on homeless population including, population size, demographic, geological location, and such; these are all vital information that are required to create resources and supports that helps to meet the needs of homeless population (Forchuk, 2021). Dr. Richard Booth’s ongoing research on homeless population enumeration aims to generate accurate quantitative representation of the homelessness incidence. It will be undertaking the form of a scoping review by reviewing relevant literatures to explore and synthesize various enumeration processes and conceptualization of construct of ‘homelessness’

Web-Based Educational Seminars Compare Favorably with In-House Seminars for Bariatric Surgery Patients

Background Comprehensive preparative patient education is a key element in bariatric patient success. The primary objective of this study was to compare attrition rates, demographics, and surgery outcomes between patients who participated in the online vs in-house preparative seminars. Methods A retrospective chart review was performed involving patients who chose to participate in online vs in-house educational seminar between July of 2014 and December of 2016. The patients were divided into two groups based on their choice of educational seminar and tracked to see how many made it to an initial visit and to surgery. In those who had bariatric surgery, data was collected on age, type of insurance, length of stay (LOS), longest follow-up, and change in body mass index. Results Total of 1230 patients were included in this study. There was no difference in attrition rate to initial consultation visit (29.1% vs 29.9%), but there was a statistically higher attrition to surgery in the in-house seminar attendees (72.9%) compared to online participants (66.6%, p < 0.05). Between January 2015 and December 2016, 291 patients underwent primary bariatric surgery. The online group was on average 3 years younger which was statistically significant. There were no differences in LOS, longest follow-up, and weight loss at 12 months between the groups. Conclusion When comparing attrition rates and bariatric surgery outcomes, no overall difference was noted between patients who received web- or hospital-based preparative education. Bariatric programs should provide access to online seminars to attract younger population and save resources and cost

Association between Medical Student Grit and United States Medical Licensing Examination Performance

Presented as Themed Oral Presentation at the 2020 IUSM Education Da

Carbon nanotube-guided thermopower waves

Thermopower waves are a new concept for the direct conversion of chemical to electrical energy. A nanowire with large axial thermal diffusivity can accelerate a self-propagating reaction wave using a fuel coated along its length. The reaction wave drives electrical carriers in a thermopower wave, creating a high-power pulse of as much as 7 kW/kg in experiments using carbon nanotubes. We review nanomaterials designed to overcome limitations of thermoelectricity and explore the emerging scientific and practical outlook for devices using thermopower waves